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We develop a general method for estimating a finite mixture of non-normalized models.
Spatial interaction and the statistical analysis of lattice systems
Besag, J · 1974
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Markov Random Field Modeling in Image Analysis
Li, S. Z · 2001
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Training products of experts by minimizing contrastive divergence
Hinton, G. E · 2002
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Energy-based models for sparse overcomplete representations
Teh, Y · 2004
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A · 2005
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Conjugate gradient algorithm
Rasmussen, C. E · 2006
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Implicit mixtures of restricted Boltzmann machines
Nair, V · 2008
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Noise-contrastive estimation: A new estimation principle for non-normalized statistical models
Gutmann, M. U · 2010
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Noise-contrastive estimation of non-normalized statistical models, with applications to natural image statistics
Gutmann, M. U · 2012
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ImageNet classification with deep convolutional neural networks
Krizhevsky, A · 2012
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Generative Adversarial Nets
Goodfellow, I · 2014
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Generative modeling of convolutional neural networks
Dai, J · 2015
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Rethinking the inception architecture for computer vision
Szegedy, C · 2015
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Unsupervised feature extraction by time-contrastive learning and nonlinear ICA
Hyvärinen, A · 2016
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A theory of generative ConvNet
Xie, J · 2016
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Nonlinear ICA of temporally dependent stationary sources
Hyvärinen, A · 2017
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